摘要
道岔控制列车的行驶方向,是轨道交通系统的关键设备.文中采用ZD7型号道岔转辙机动作电流数据,提出基于快速动态时间规整算法(FastDTW)的道岔故障智能诊断方法.根据原始电流曲线特性将曲线分段处理,通过FastDTW计算待诊断电流曲线与模板电流曲线的扭曲路径距离,根据动态确定的最优阈值诊断故障.实验表明,该方法可适用于单动、双动型号道岔故障诊断问题,仅需200条道岔动作电流历史数据.该方法诊断准确率较高,时间较短,也适用于准确性、实时性要求较高的新型列控系统.
The turnout handles the direction of the train.It is a key equipment for the safety of railway transportation system.An intelligent fault diagnosis method based on fast dynamic time warping(FastDTW)for railway turnout is proposed in this paper.It is testified by the real action current data obtained from switch machine model No.ZD7.Firstly,the original current curve is segmented according to wave form features.Then,the warp path distance between the standard sample and the tested current curve is obtained by FastDTW algorithm.Finally,a dynamic optimized threshold is exploited to confirm whether there is a fault in the turnout.The experimental results show the proposed method works well with both single and double action type turnout machines with only 200 turnout action current samples.The proposed method is suitable for the train control system of new generation as well due to its high diagnosis accuracy and low time cost.
作者
姬文江
左元
黑新宏
高橋聖
中村英夫
JI Wenjiang;ZUO Yuan;HEI Xinhong;SEI Takahashi;HIDEO Nakamura(Faculty of Computer Science and Engineering,Xi′an University of Technology,Xi′an 710048;Department of Computer Engineering,Nihon University,Funabashi 274-8501;Graduate School of Frontier Science,The University of Tokyo,Tokyo 113-8656)
出处
《模式识别与人工智能》
EI
CSCD
北大核心
2020年第11期1013-1022,共10页
Pattern Recognition and Artificial Intelligence
基金
国家重点研发计划项目(No.2018YFB120500)
国家自然科学基金项目(No.61773313,61702411)资助。